Bayesian Combination of Weighted Principal-Component Analysis for Diagnosing Sensor Faults in Structural Monitoring Systems-Reference-Cited by-同舟云学术

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Bayesian Combination of Weighted Principal-Component Analysis for Diagnosing Sensor Faults in Structural Monitoring Systems

Published:2017-09 Issue:9 Volume:143 Page:04017088
ISSN:0733-9399
Container-title:Journal of Engineering Mechanics
language:en
Short-container-title:J. Eng. Mech.

Author:

Huang Hai-Bin¹,Yi Ting-Hua²,Li Hong-Nan³

Affiliation:

1. Ph.D. Candidate, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China.

2. Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China (corresponding author).

3. Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Mechanics of Materials

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EM.1943-7889.0001309

Reference49 articles.

1. Extended blind modal identification technique for nonstationary excitations and its verification and validation;Abazarsa F.;J. Eng. Mech.,2015

2. Sensor validation for structural systems with additive sensor faults;Abdelghani M.;Struct. Health Monit.,2004

3. Sensor validation for structural systems with multiplicative sensor faults;Abdelghani M.;Mech. Syst. Signal Process.,2007

4. Analysis and generalization of fault diagnosis methods for process monitoring;Alcala C. F.;J. Process Control,2011

5. Modeling, Detection, and Disambiguation of Sensor Faults for Aerospace Applications

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